“You really can’t say that, since CBT emerged in 2007 and 2008 and markets have been very volatile, that CBT is wrong,” Zigrand argues. “We had to try to commission papers that were able to control for the financial crisis to see what the net effect of CBT is.”

The report found HFT has contributed to falling transaction costs, linked fragmented markets together and allowed for information on prices to be delivered more rapidly.

Liquidity has also improved as a result of HFT, with high-frequency traders now providing the bulk of liquidity. The report did note, however, that their use of limited capital combined with ultra-fast speed creates the potential for periodic illiquidity.

CBT has also improved market efficiency by creating predictability in order flows through computer-driven portfolio rebalancing and deterministic algorithms. The study warns this does leave the door open for new forms of market manipulation, although no direct evidence suggests HFT has increased market abuse.

Claims of market manipulation using HFT techniques are nonetheless often reported by institutional investors across the globe. These investors say they have little or no confidence in the ability of regulators to curb market abuse. This loss of confidence should be taken seriously, with the report recommending regulators increase their efforts to detect abuse and produce statistical evidence on its extent.

Zigrand praises CBT’s “solid risk limits and beautifully risk-managed systems”. However, while there is no direct evidence suggesting HFT has increased volatility, instabilities can nonetheless occur in specific circumstances. The study highlighted two possible causes of crashes and large swings in the market: the normalisation of deviance and self-reinforcing feedback loops.

Feedback loops in CBT can occur at a speed that is a great deal faster than the reaction times of humans. Computers also lack a key strength to potentially prevent feedback loops: common sense.

“The normalisation of deviance is another feedback loop, but it’s a very slow-moving feedback loop,” says Zigrand. It is a social issue, where unexpected events come to be seen as normal until a disastrous failure occurs.

CBT creates environments that can worsen feedback loops. A key risk is the loss of market diversity in CBT. Market participants often adopt the same lines of code in the race for speed, or have similar risk-management systems, regulatory constraints, margin calls and mark-to-market accounting requirements.

“During an event you have no diversity,” says Zigrand. “If this means they have to sell, then they all sell. If it means they have to buy, then they all buy. There can be periods of time where no divergence of opinion of a human comes in and algorithms just effectively have the same strategy.” Similar behaviour by a large number of portfolio insurance mechanisms has been blamed for the 1987 stock market crash.

Information issues also pose a potential danger within CBT environments. Technology has further removed, to a certain extent, common knowledge from markets. Markets have become distributed computing environments, potentially introducing an obfuscatory layer between events and decisions.

Looking forward, the report outlines the development of ‘anti-traders’ as a possible risk. As trading is increasingly done by algorithms, the role of a trader is simply to shut trading engines down as well as tweak them, rather than take decisions. This can result in fewer risks being identified early on, as traders become less actively involved in observing the markets.

The importance of HFT is certainly growing, now representing around 30% of equity trading in the UK, compared with an estimated 60% in the US. Profits of high-frequency traders in the US were estimated at $7.2 billion in 2009. By comparison, the total value of electronic order book share trading on the NYSE and Nasdaq exchanges in New York during 2009 was in excess of $30 trillion.